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About

Sofia Yousuf is a robotics and autonomous systems researcher whose work centers on mobile robot localization, sensor fusion, and navigation — fields critical to the advancement of intelligent robotic systems. She is best known for her contributions to multisensor fusion frameworks that integrate GPS, Inertial Navigation Systems (INS), and odometer data to achieve robust and accurate robot localization across both indoor and outdoor environments. Her 2020 paper on information fusion of these three sensor modalities has garnered 33 citations, establishing it as a key reference in the field, while her earlier 2016 work on Kalman Filter-based sensor fusion has accumulated 26 citations, reflecting sustained community interest in her methodological approaches. Beyond localization, Yousuf has extended her research into robot navigation, developing implementations of the Tangent Bug algorithm for obstacle avoidance across multiple robot drive configurations. Her more recent work on trajectory tracking control of robotic arms — combining inverse dynamics modeling with fuzzy gain scheduling and experimental validation — signals a broadening research scope into robotic manipulation and control systems. Across her career, Yousuf's publications reflect a consistent commitment to bridging theoretical rigor with practical implementation, making her work particularly valuable for engineers and researchers developing real-world autonomous robotic systems.